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Related Experiment Video

Updated: Jun 27, 2026

Robotic-assisted Bronchoscopy Combined with Multimodal Imaging for Targeted Lung Cryobiopsies

Robotic-assisted Bronchoscopy Combined with Multimodal Imaging for Targeted Lung Cryobiopsies

Published on: July 19, 2024

Image-based reporting for bronchoscopy.

Kun-Chang Yu¹, Jason D Gibbs, Michael W Graham

¹Endographics Imaging Systems, State College, PA 16801, USA.

Journal of Digital Imaging

|December 4, 2008

Summary

This summary is machine-generated.

This study introduces a new method for planning lung cancer bronchoscopy using patient-specific CT scans. The developed reports provide virtual previews, improving procedural planning and guidance for diagnosing peripheral lung nodules.

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Robotic-assisted Bronchoscopy Combined with Multimodal Imaging for Targeted Lung Cryobiopsies

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Optical Frequency Domain Imaging of Ex vivo Pulmonary Resection Specimens: Obtaining One to One Image to Histopathology Correlation

Optical Frequency Domain Imaging of Ex vivo Pulmonary Resection Specimens: Obtaining One to One Image to Histopathology Correlation

Published on: January 22, 2013

Area of Science:

Pulmonology
Medical Imaging
Interventional Oncology

Background:

Bronchoscopy is crucial for lung cancer staging, but planning procedures for peripheral lesions is challenging.
Current planning methods are time-consuming and prone to errors.
Advancements in multidetector computed tomography (MDCT) and ultrathin bronchoscopes allow for peripheral lesion biopsy.

Purpose of the Study:

To develop and evaluate a novel method for generating patient-specific reports to aid bronchoscopic procedure planning.
To provide quantitative data and virtual previews of bronchoscopic routes for improved navigation.

Main Methods:

A new method was developed to create preview reports for bronchoscopic procedures using MDCT chest scans.
Reports include quantitative data, static and dynamic virtual endoluminal renderings, and 3D cues for biopsy sites.
The system was tested in a pilot study with 22 lung cancer patients.

Main Results:

Generated reports for 22 patients, utilizing them for guidance in 17 cases.
The system enabled effective procedure preview and strategy planning.
Reports require minimal storage and computational resources, suitable for portable devices.

Conclusions:

The proposed reporting system significantly enhances the planning and guidance of bronchoscopic procedures for lung cancer diagnosis.
Virtual previews and quantitative data improve navigation accuracy to peripheral regions of interest.
This tool offers a practical solution to the difficulties associated with traditional bronchoscopic planning.